CT-ISG Security and Privacy of Biometric Templates: Theory and Practice

CT-ISG 生物识别模板的安全性和隐私性：理论与实践

• 批准号: 0716490
• 负责人: Nasir Memon
• 金额: $ 20万
• 依托单位: Polytechnic University of New York
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-01 至 2010-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0716490&HistoricalAwards=false
• 关键词: CT; ISG; Security; Privacy; Biometric

The main objective of this project is to develop simple, practical and provably effective cryptographic techniques for the security and privacy of biometric data. The proposed research will formulate rigorous notions of security and privacy for real world biometric data, which may be continuous and with complex similarity measures. This will be done by developing error-tolerant techniques that can be applied to achieve the targeted security and privacy requirements. The proposed approach is mainly based on recent devel-opments in error-tolerant cryptography centered around the idea of a secure sketch. In fact, well known error tolerant schemes like fuzzy commitment and fuzzy vault can be considered as special cases of the general notion of secure sketch. The secure sketch framework is a promising approach for protecting biometric data. Not only is it more amenable to combination with signal processing techniques for application to real biometric data, but it also provides provable security under reasonable assumptions. The techniques developed will be implemented and an investigation of their performance in terms of false accepts and false rejects will be carried out along with and analysis of the trade-off between the performance and the security. Practical cryptographic protocols for biometric applications under a variety of threat models will also be developed. Furthermore, techniques to enhance security using multimodal biometrics and/or multi-factor schemes will be studied.

该项目的主要目标是为生物特征数据的安全和隐私开发简单、实用和被证明有效的加密技术。这项拟议的研究将为现实世界的生物识别数据制定严格的安全和隐私概念，这些数据可能是连续的，具有复杂的相似性衡量标准。这将通过开发可应用于实现目标安全和隐私要求的容错技术来实现。该方法主要基于以安全草图为核心的容错密码学的最新发展。事实上，著名的容错方案，如模糊承诺和模糊保险库，可以被认为是一般安全草图概念的特例。安全草图框架是保护生物特征数据的一种很有前途的方法。它不仅更易于与信号处理技术相结合来应用于真实的生物特征数据，而且在合理的假设下还提供了可证明的安全性。将实施开发的技术，并将调查其在错误接受和错误拒绝方面的性能，并对性能和安全性之间的权衡进行分析。还将开发实用的密码协议，用于各种威胁模式下的生物识别应用。此外，还将研究使用多模式生物识别和/或多因素方案来增强安全性的技术。